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System Architecture

Architecture Patterns

"Patterns are solutions to recurring problems. Use them wisely, adapt them to context, but never apply them blindly."

Pattern Philosophy

Architecture patterns are not blueprints—they're templates. Each must be adapted to your specific constraints, team capabilities, and business requirements.

We document patterns not to prescribe solutions, but to create a shared vocabulary. When we say "circuit breaker," everyone understands the trade-offs, failure modes, and implementation considerations.

Core Architectural Patterns

Microservices Architecture

Decompose applications into small, independently deployable services organized around business capabilities.

When to Use

  • • Large, complex systems
  • • Multiple teams
  • • Independent scaling needs

Trade-offs

  • • Operational complexity
  • • Network latency
  • • Distributed debugging

Key Considerations

  • • Service boundaries
  • • API contracts
  • • Data consistency

Event-Driven Architecture

Components communicate through asynchronous events, enabling loose coupling and reactive behavior.

When to Use

  • • Real-time processing
  • • Decoupled systems
  • • Asynchronous workflows

Trade-offs

  • • Eventual consistency
  • • Event ordering challenges
  • • Debugging complexity

Key Considerations

  • • Event schema design
  • • Event versioning
  • • Message durability

CQRS (Command Query Responsibility Segregation)

Separate read and write operations into distinct models optimized for their specific use cases.

When to Use

  • • Complex read/write patterns
  • • High read/write disparity
  • • Performance optimization

Trade-offs

  • • Increased complexity
  • • Data synchronization
  • • Eventually consistent reads

Key Considerations

  • • Sync mechanisms
  • • Model design
  • • Consistency requirements

Saga Pattern

Manage distributed transactions through a sequence of local transactions with compensating actions for rollback.

When to Use

  • • Distributed transactions
  • • Cross-service workflows
  • • Long-running processes

Trade-offs

  • • Compensation logic complexity
  • • Partial failure handling
  • • Monitoring challenges

Key Considerations

  • • Idempotency
  • • Compensation design
  • • State management

Circuit Breaker Pattern

Prevent cascading failures by stopping requests to failing services and allowing them time to recover.

When to Use

  • • External service calls
  • • Fault-prone operations
  • • Resilience requirements

Trade-offs

  • • False positives
  • • Configuration complexity
  • • Monitoring overhead

Key Considerations

  • • Threshold tuning
  • • Fallback strategies
  • • Recovery detection

API Gateway Pattern

Single entry point for all clients, handling routing, authentication, rate limiting, and request aggregation.

When to Use

  • • Multiple microservices
  • • Client diversity
  • • Cross-cutting concerns

Trade-offs

  • • Single point of failure
  • • Latency addition
  • • Scaling bottleneck

Key Considerations

  • • High availability
  • • Performance optimization
  • • Security hardening

Pattern Anti-Patterns

Resume-Driven Architecture

Choosing patterns because they're trendy, not because they solve your specific problem. Microservices aren't always the answer.

Pattern Overload

Applying every pattern you know to a simple problem. Sometimes a monolith is the right choice. Start simple, evolve as needed.

Cargo Cult Architecture

Copying Netflix's architecture because "it worked for them." Your constraints, scale, and team are different. Adapt, don't copy.

Premature Distribution

Breaking up a system before understanding its boundaries. Start with a well-structured monolith. Split when you have evidence it's needed.